دورية أكاديمية
G.A.M.E.: GPU-accelerated mixture elucidator
| العنوان: | G.A.M.E.: GPU-accelerated mixture elucidator |
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| المؤلفون: | Alioune Schurz, Bo-Han Su, Yi-Shu Tu, Tony Tsung-Yu Lu, Olivia A. Lin, Yufeng J. Tseng |
| المصدر: | Journal of Cheminformatics, Vol 9, Iss 1, Pp 1-9 (2017) |
| بيانات النشر: | BMC, 2017. |
| سنة النشر: | 2017 |
| المجموعة: | LCC:Information technology LCC:Chemistry |
| مصطلحات موضوعية: | Natural product, Mass spectrum, Structure elucidator, GPU acceleration, Information technology, T58.5-58.64, Chemistry, QD1-999 |
| الوصف: | Abstract GPU acceleration is useful in solving complex chemical information problems. Identifying unknown structures from the mass spectra of natural product mixtures has been a desirable yet unresolved issue in metabolomics. However, this elucidation process has been hampered by complex experimental data and the inability of instruments to completely separate different compounds. Fortunately, with current high-resolution mass spectrometry, one feasible strategy is to define this problem as extending a scaffold database with sidechains of different probabilities to match the high-resolution mass obtained from a high-resolution mass spectrum. By introducing a dynamic programming (DP) algorithm, it is possible to solve this NP-complete problem in pseudo-polynomial time. However, the running time of the DP algorithm grows by orders of magnitude as the number of mass decimal digits increases, thus limiting the boost in structural prediction capabilities. By harnessing the heavily parallel architecture of modern GPUs, we designed a “compute unified device architecture” (CUDA)-based GPU-accelerated mixture elucidator (G.A.M.E.) that considerably improves the performance of the DP, allowing up to five decimal digits for input mass data. As exemplified by four testing datasets with verified constitutions from natural products, G.A.M.E. allows for efficient and automatic structural elucidation of unknown mixtures for practical procedures. Graphical abstract . |
| نوع الوثيقة: | article |
| وصف الملف: | electronic resource |
| اللغة: | English |
| تدمد: | 1758-2946 |
| Relation: | http://link.springer.com/article/10.1186/s13321-017-0238-7; https://doaj.org/toc/1758-2946 |
| DOI: | 10.1186/s13321-017-0238-7 |
| URL الوصول: | https://doaj.org/article/51f14e21017d452d856451d4491a1a05 |
| رقم الأكسشن: | edsdoj.51f14e21017d452d856451d4491a1a05 |
| قاعدة البيانات: | Directory of Open Access Journals |
Find this article in full text from Springer Verlag. 
Full Text Finder | تدمد: | 17582946 |
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| DOI: | 10.1186/s13321-017-0238-7 |